摘要
穗位叶光合相关参数状况直接影响玉米后期产量构成,探讨高光谱遥感数据与叶片光合相关参数的关系,对快速,准确评价玉米穗位叶光合特性状况具有重要的意义。通过设置4个不同氮肥水平(N0:0 kg/hm2,N1:170 kg/hm2,N2:340 kg/hm2,N3:500 kg/hm2),以抽雄吐丝期玉米穗位叶为研究对象,分析叶片净光合速率(Pn)、气孔导度(Gs)、蒸腾速率(Tr)等光合参数,PSⅡ最大光化学效率(Fv/Fm)、PSⅡ实际光化学效率(ΦPSⅡ)、吸收的光能被用于光化学反应的份额(P)、非光化学淬灭系数(NPQ)等荧光参数,叶绿素含量(Chl)、类胡萝卜素含量(Cars)、叶绿素含量/类胡萝卜素含量(Chl/Cars)等光合色素参数以及光谱反射率的变化规律,明确光合荧光相关参数与原始光谱反射率、一阶微分光谱、植被指数等高光谱数据之间的关系。结果表明,Pn、Tr、Fv/Fm、ΦPSⅡ、P、Chl、Cars、Chl/Cars等8个参数随着氮肥的增加呈现上升趋势,与对照相比差异显著(P<0.05),而Gs和NPQ在各处理下差异不显著(P>0.05),NPQ随着氮肥的增加呈现先减小后增大的趋势。对于光谱反射率,可见光波段光谱反射率随着氮肥的增加而降低,近红外波段施肥处理反射率比未施氮肥处理显著升高,红边位置出现"红移"现象。通过Pn、Tr、Fv/Fm、ΦPSII、P、NPQ、Chl、Cars、Chl/Cars与原始、微分光谱及植被指数相关性分析,最佳高光谱变量分别为Dλ699、Dλ701、Dλ703、Dλ702、Dλ701、R764、Dλ699、Dλ699、Dλ700,相关系数分别为0.81、-0.73、-0.54、-0.58、-0.61、-0.49、-0.996、-0.997、-0.877,均达到了极显著水平(P<0.01);而Gs的相关性最佳高光谱变量为Dλ575,相关系数为0.47(P<0.05)。因此,利用高光谱遥感技术评价玉米抽雄吐丝期穗位叶光合荧光相关参数具有可行性,对评价玉米后期产量构成具有重要的意义。
Photosynthesis of ear-leaf directly affects yield of maize in the late period, it is of great significance for evaluating photosynthesis quickly and accurately by analyzing the relationship between hyperspectral remote sensing data and photosynthetic related parameters. In this research, four different N levels （NO： 0 kg/hm^2, NI： 170 kg/hm^2, N2：340 kg/hm^2, N3：500 kg/hm^2） were used to analyze the change trends of photosynthetic parameters, chlorophyll fluorescence parameters, photosynthetic pigments and spectra/ reflectance of maize ear-leaf, and to discuss the relationship between photosynthetic fluorescence narameters and reflectance data. The results showed that Pn, Tr, Fv/Fm, φPPS Ⅱ, P, Chl, Cars, ChllCars increased with increasing N level, and there were significant differences compared with NO treatment （P〈0.05）, while Gs and NPQ had no difference among all treatments （P〉0.05）. With a rise of N treatment rate, spectral reflectance decreased in visible wavelength with increasing N level, opposite trends were found in near-infrared region. In addition, the red edge position moved to red wavelength with increasing N level. According to the correlation analysis of hyperspectral reflectance, first derivative spectrum, vegetation index and Photosynthetic Fluorescence Parameters, the optimal-hyperspectral variable of Pn, Tr, Fv/Fm, φPSⅡ, P, NPQ, Chl, Cars and Chl/Cars was Dλ699, Dλ701,, Dλ703, Dλ702, DλA701, R764, Dλ699, Dλ699 and DAλ700 respectively. And the corresponding correlation coefficient was 0.81,-0.73,-0.54,-0.58,-0.61,-0.49,-0.996,-0.997 and-0.877 （P〈0.01）. The optimal hyperspectral variable for Gs was Dλ75 （P〈0.05）. Therefore, it was possible to assessing photosynthetic fluorescence parameters using hyperspectral remote sensing data, and it would be of great significance for analyzing yield of maize in the late period of the growing cycle.
出处
《中国农学通报》
2015年第24期71-77,共7页
Chinese Agricultural Science Bulletin
基金
农业部公益性行业科研专项资金项目"主要农作物高产高效生理基础及栽培新技术研究与应用"(201203096)
四川农业大学大学生创新性实验"基于农业物联网视觉技术的玉豆氮营养诊断方法研究"(00109253)
关键词
高光谱
光合
叶绿素荧光
光合色素
遥感
hyperspectra
photosynthesis
chlorophyll fluorescence
photosynthetic pigments
remote sensing
